Triple

T29693082
Position Surface form Disambiguated ID Type / Status
Subject Ran E751264 entity
Predicate borderRegionOf P10768 FINISHED
Object Kartvelian polities
Kartvelian polities were historical Georgian and related Caucasian states that emerged in the South Caucasus, sharing common Kartvelian cultural and linguistic roots.
E1878325 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Kartvelian polities | Statement: [Ran, borderRegionOf, Kartvelian polities]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Kartvelian polities
Triple: [Ran, borderRegionOf, Kartvelian polities]
Generated description
Kartvelian polities were historical Georgian and related Caucasian states that emerged in the South Caucasus, sharing common Kartvelian cultural and linguistic roots.

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69f0d625b09481909b0b69aea1e846c8 completed April 28, 2026, 3:45 p.m.
NER Named-entity recognition batch_69f672963f0481909795a3384a2d3bb4 completed May 2, 2026, 9:54 p.m.
NED1 Entity disambiguation (via context triple) batch_6a267ece7cf081908f27f9faa9b73653 completed June 8, 2026, 8:35 a.m.
NEDg Description generation batch_6a2684b776d481909718eaa128bb736a completed June 8, 2026, 9 a.m.
NED2 Entity disambiguation (via description) batch_6a2688aa26ec8190a39595ce2317d128 completed June 8, 2026, 9:17 a.m.
Created at: April 28, 2026, 7:18 p.m.